Learning from Learning from Model-Produced Graphs Model-Produced Graphs

in a Climate Change Science Class in a Climate Change Science Class

Catherine Gautier

Geography Department

UC Santa Barbara

GraphsGraphs

• Graphs are commonly used in geoscience courses

• Graphs help students understand geoscience, quantitative information and scientific reasoning

Some students have difficulties comprehending Some students have difficulties comprehending information depicted in some geoscience graphsinformation depicted in some geoscience graphs

Should students be at ease with simple visual representations like graphs, maps, charts before more sophisticated visual representations such as animations or

3-D representations are presented to them?

What is the role of graphs What is the role of graphs in learning climate sciencein learning climate science

Communicate relevant quantitative

information

Promote thinking about data and scientific information

Comprehension Scientific Reasoning

Dealing with quantitative information

Cognitiveaspects

Graphs and Graphs and Scientific ReasoningScientific Reasoning

• Ability to think about data by relating them to: theories, conclusions, hypotheses, explanations

– What kind of tasks promote students’ ability to explain data and relate data to theories and hypotheses?

• Ability to ask the “right” question– Do certain kinds of graphs support reasoning

about the “right” questions?– Can graphs highlight questions students might

ask and therefore promote scientific reasoning skills?

Experiment and Data CollectionExperiment and Data CollectionModel-based Inquiry CourseModel-based Inquiry Course

• Student-generated scientific question and experimental design

• Student-performed experiment with model• Graphs and data tables generation• Graphs integration into a scientific reasoning• Students- produced graphics analyzed to

evaluate – students’ ability to comprehend graphs and interpret quantitative

information (display quantitative skills)– Graphs’ role in helping students’ thinking about data and in

promoting scientific inquiry (asking “right” question)

Multimedia DisplayMultimedia Display

Multimedia display – Visual and textual– Interaction of task and graphic format– Complementarity of graphical presentation

forms: integrative with graph and separative with table

Visual characteristics of graphic display

– 2-D format– Line graph (suggests continuity of vertical

distribution and provide trend)– Multiple lines for comparisons– Simple mapping between referent (flux) and

variable altitude, wavelength, time, sun angle

Table– To get single point value (surface)– To extract data for additional (external)

visualizationText

– To explain how model works– To describe inputs and outputs

Experiment and Data CollectionExperiment and Data CollectionModel-based Inquiry CourseModel-based Inquiry Course

• Student-generated scientific question and experimental design

• Student-performed experiment with model• Graphs and data tables generation• Graphs integration into scientific reasoning• Students-produced graphics analyzed to

evaluate – Students’ ability to interpret quantitative information (display

quantitative skills)– Graphs’ role in helping students’ thinking about data and in

promoting scientific inquiry (asking “right” question)

Analysis of GraphsAnalysis of Graphs

• Two types of graphs – model-produced – student-produced (advanced investigations)

• Graph interpretation: graphs and quantitative skills

• Graphs and scientific reasoning: analytical representation of results for theory establishment or verification

• Graphs and scientific reasoning: asking “right” question

Student-Produced GraphsStudent-Produced Graphs

Optical Thickness vs. Flux Down at the Surface

y = 1044e-0.0754x

R2 = 0.9972

0

200

400

600

800

1000

1200

0 2 4 6 8 10 12

Optical Thickness

Flu

x D

ow

n (

W/m

^2)

UV-B Flux Down at the Surface vs. Time of Day

0

2

4

6

8

10

12

4 9 14 19

Time of Day (hours)

To

tal F

lux

(W/m

^2)

Snow Grass Sand Sea Water

Data extraction from tableproduced by a series of runs

From sensitivityexperiments

From one experiment

Analysis of GraphsAnalysis of Graphs

• Two types of graphs – model-produced – student-produced (advanced investigations)

• Graph interpretation: graphs and quantitative skills

• Graphs and scientific reasoning: analytical representation of results for theory establishment or verification

• Graphs and scientific reasoning: asking “right” question

Graphs Interpretation and Graphs Interpretation and Quantitative SkillsQuantitative Skills

Quantitative skills Frequency of use in

graph interpretationEstimating 10-15%

Phenomena Quantification 99% (required)

Hypothesis evaluation 98% (required)

Processes Quantification/explanation ~25%

Graphic Production ~10%

Advanced mathematical/statistical modeling

~5%

Analysis of GraphsAnalysis of Graphs

• Two types of graphs – model-produced – student-produced (advanced investigations)

• Graph interpretation: graphs and quantitative skills

• Graphs and scientific reasoning: analytical representation of results for theory establishment or verification

• Graphs and scientific reasoning: asking “right” question (talk on Thursday morning)

Theory Verification or Theory Verification or EstablishmentEstablishment

Theory Verification

instructor

Theory Establishment

Scattered Radiation vs. Wavelength

y = 5.4157x-3.9746

R2 = 0.6567

0.00

100.00

200.00

300.00

400.00

500.00

600.00

700.00

800.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

wavelength

Sa

ctt

ere

d R

ad

iati

on

Scattered RadiationPower (Scattered Radiation)

Optical Thickness vs. Flux Down at the Surface

y = 1044e-0.0754x

R2 = 0.9972

0

200

400

600

800

1000

1200

0 2 4 6 8 10 12

Optical Thickness

Flu

x D

ow

n (

W/m

^2)

Theory Verification

Noisy data from model?

SummarySummary

• Importance of repetitive nature of tasks and graphs produced to graph comprehension– Development of graph schema for lower performing students

• Graph interpretation and quantitative skills– Required quantitative skills related to the use of graphs well

grasped– Other quantitative skills only employed by best students

• Graphs allowed students to visualize and communicate quantitative information and this promoted thinking about data

• Through the interaction between graphs and quantitative skills, the class activities supported the application and development of scientific reasoning including – theory validation or establishment, hypothesis testing– Asking valid scientific questions

Future ResearchFuture Research• Assessment

– Scientific reasoning cognitive level in climate change science– Students’ graph comprehension/schema prior and after class– Interaction between graph schema and content knowledge

• Develop series of focused questions– What are the main characteristics of the “relevant” information that need to be

communicated in climate change? What makes a graph better or worse at communicating relevant quantitative information in climate change?

– How do students comprehend graphs and what are the factors that influence students’ interpretations?

– How might different ways in which data are manipulated promote thinking about data?

– How do individual differences in graph reading skills and domain knowledge influence the kinds of interpretations that students give graphs presented to them?

• Develop customized tools for assessment– Develop multiple assessment approach and Integrate results from different tools– For each question develop appropriate tool (questionnaires, video and audio

recording, analysis of written and presented work, concept maps)